Senior Applied Scientist
Microsoft
Senior Applied Scientist
Redmond, Washington, United States
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Overview
Microsoft is a company where passionate innovators come to collaborate, envision what can be and take their careers further. This is a world of more possibilities, more innovation, more openness, and the sky is the limit thinking in a cloud-enabled world.
Microsoft’s Azure Data engineering team is leading the transformation of analytics in the world of data with products like databases, data integration, big data analytics, messaging & real-time analytics, and business intelligence. The products our portfolio include Microsoft Fabric, Azure SQL DB, Azure Cosmos DB, Azure PostgreSQL, Azure Data Factory, Azure Synapse Analytics, Azure Service Bus, Azure Event Grid, and Power BI. Our mission is to build the data platform for the age of AI, powering a new class of data-first applications and driving a data culture.
Within the Microsoft Fabric product pillar, the Real‑Time Intelligence (RTI) team is hiring a Principal Applied Scientist to lead real‑time ML that powers agentic workflows on live operational data, driving capabilities such as autonomous agents, anomaly detection at scale, and decisioning that closes the loop from detection to action. What makes RTI unique is its deep integration across Fabric’s real‑time surfaces (e.g., KQL/RT dashboards, streaming pipelines, and Data Activator), a human‑in‑the‑loop design for trustworthy detections, and shared ML components that let us ship science rapidly across multiple experiences. In this role, you’ll partner closely with engineering to architect low‑latency inference, rigorous evaluation, and production monitoring for ML/LLM systems, owning the science from research through deployment and continuous improvement.
We do not just value differences or different perspectives. We seek them out and invite them in so we can tap into the collective power of everyone in the company. As a result, our customers are better served.
Qualifications
Required/Minimum Qualifications
- Bachelor's Degree in Statistics, Computer Science, Electrical or Computer Engineering, or related field and 4+ years related experience OR
- OR Master's Degree in Statistics, Computer Science, Electrical or Computer Engineering, or related field and 3+ years related experience
- OR Doctorate in Statistics, Computer Science, Electrical or Computer Engineering, or related field and 1+ years related experience
- OR equivalent experience.
- Experience applying machine learning and statistical methods to real‑time or streaming data scenarios, with a track record of delivering production‑grade solutions.
- Proficiency in agentic AI concepts (e.g., autonomous agents, orchestration frameworks) and familiarity with anomaly detection and causal inference techniques.
Other Requirements
- Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings: Microsoft Cloud Background Check:
- This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
Preferred/Additional Qualifications
- Proven experience applying machine learning and statistical methods to real‑time or streaming data scenarios, with a track record of delivering production‑grade solutions.
- Proficiency in agentic AI concepts (e.g., autonomous agents, orchestration frameworks) and familiarity with anomaly detection and causal inference techniques.
- Strong programming and modeling skills in languages such as Python or C#, and experience with distributed systems or low‑latency inference pipelines.
- Ability to design and evaluate models rigorously, including offline metrics, online experimentation, and reliability monitoring at scale.
- Collaborative mindset with demonstrated success partnering across engineering, product, and UX teams to translate research into impactful customer experiences.
- Commitment to responsible AI practices, inclusive design, and continuous learning in emerging ML/LLM technologies.
Applied Sciences IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $158,400 - $258,000 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay
Microsoft will accept applications for the role until October 29, 2025.
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Responsibilities
- Lead end‑to‑end science for real‑time ML/LLM systems that power agentic workflows on streaming data: designing reliable, low‑latency inference and partnering with engineering for robust deployment and operations.
- Advance anomaly detection and causal insights across RTI surfaces by driving model selection, human‑in‑the‑loop feedback, and measurable lifts in precision/recall and time‑to‑detection.
- Establish rigorous evaluation and reliability practices: from offline metrics and online experiments to production monitoring and guardrails, balancing quality with cost/latency at scale.
- Collaborate with PM, Engineering, and UX to translate research into customer‑visible scenarios and outcomes, iterating quickly based on telemetry and user feedback.
- Provide technical leadership and mentorship within the applied science community, fostering inclusive, responsible‑AI practices and influencing roadmap and cross‑team strategy.